LLVM-AD @ WACV 2026

About the Workshop

The 5th Workshop on Large Language and Vision Models for Autonomous Driving (LLVM-AD) at WACV 2026 aims to bring together professionals from academia and industry to explore the applications of large language and vision models in autonomous driving. We are particularly interested in bridging the gap between the rich image and language data found within the context of autonomous driving. Our primary areas of interest are: a) Traffic Scene Understanding enhanced by VLMs and b) Human-Autonomy Teaming driven by LLMs. The topics include but not limited to

Large Language Models and Vision Language Models for Autonomous Driving
Multimodal Motion Planning and Prediction
New Dataset for Autonomous Driving
Semantics and Scene Understanding in Autonomous Driving
Language-Driven Sensor and Traffic Simulation
Domain Adaptation and Transfer Learning in Autonomous Driving
Multi-Modal Fusion for Autonomous Driving
Survey and Prospective Paper for Autonomous Driving
Other Applications of Language or Vision Models for Driving

The schedule will be available here.

Accepted Papers

🎉 We would like to congrats the following papers for being accepted to 5th LLVM-AD!

Lightweight Multi-Scale Fusion for Real-Time Autonomous Driving Segmentation
FROST-Drive: Scalable and Efficient End-to-End Driving with a Frozen Vision Encoder
Efficient Visual Question Answering Pipeline for Autonomous Driving via Scene Region Compression
Benchmarking Vision-Language Models for Traffic Scene Understanding in Inclement Winter Weather: The AWDB Benchmark
Role of Language-Guidance in Knowledge Distillation for Semantic Segmentation Under Limited Field-Of-View Autonomous Driving
Less Is More: Agentic Prompt Design for Safe VLM Action Selection
Trust-Guided Multimodal LLM Integration with Reinforcement Learning for Autonomous Driving
VLA4CoDrive: Vision–Language–Action Dataset for Cooperative Autonomous Driving
2COOOL: An Evaluation Benchmark for Generating Incident Reports on Out-of-Distribution Hazards in Autonomous Driving
GATEPose: A Graph Attention Transformer Enhanced with Pose and Orientation Angles for Pedestrian Crossing Intention Prediction

Call for Papers

The workshop papers will be published in IEEE Xplore as WACV 2026 Workshop Proceedings and will be indexed separately from the main conference proceedings. The papers submitted to the workshop should follow the same formatting requirements as the main conference.

The manuscripts should be of 6 to 8 pages. Submissions are expected to follow the same guidelines as those for WACV’s main conference papers.

Please refer to page of call for papers for more details.